Data Catalog Product VP

The Chief Data and Analytics Office (CDAO) builds enterprise-scale platforms for Data Management, Analytics, and AI/ML Operations used firm-wide across JPMorgan Chase. Within CDAO, the Data for AI Product Management team creates reusable platform solutions that transform how data producers and consumers discover, access, govern, and leverage data.

As the Data Catalog Product Manager, you will play a pivotal role in building a unified, multi-channel data marketplace where thousands of firmwide datasets become easy to find, preview, and integrate across application and AI use cases. You will own the end-to-end vision, strategy, and execution - spanning a rich web UI, programmatic APIs, and future agentic integrations (Claude, Copilot, internal AI assistants) that meet consumers where they already work.

We want someone who leads with problems, not solutions - who brings deep UX and service design expertise, has built catalog or marketplace products at scale, and can articulate how intelligent discovery evolves in an agentic AI world.

• Define the multi-year product vision and roadmap for firmwide data discovery serving data scientists, ML engineers, analytics engineers, and increasingly business users.
• Establish north-star metrics tied to real impact: time-to-data, publishing velocity, discovery-to-integration conversion, repeat usage, and governance compliance.
• Own the full lifecycle from problem discovery → delivery → adoption → iteration.

• Lead the UX and service design vision - intuitive, fast, and delightful across all touchpoints.
• Build rich dataset pages with metadata, schema previews, sample data, interactive code samples, lineage, quality scores, usage stats, ratings, and community annotations - inspired by the best consumer marketplace patterns (Kaggle, Spotify, App Store).

• Architect an API-first platform powering a beautiful web UI today and programmatic access for code-first engineers.
• Meet consumers in their daily tools - notebooks, IDEs, orchestration platforms, chat interfaces, copilots - eliminating context-switching.
• Design composable, reusable solutions that integrate with the broader CDAO ecosystem.

• Producers: Make it effortless to publish, document, version, and maintain datasets with rich metadata, automated quality profiling, and governance guardrails.
• Consumers: Reduce friction from discovery to access - self-service provisioning, entitlement workflows, one-click integration with SageMaker, Databricks, and EMR.
• Network effects: Analyze usage trends to improve data quality, discovery and relevancy across persona groups

• Work with UX designers and researchers on usability testing, rapid prototyping, and user validation.
• Write detailed PRDs and technical documentation that engineers and consumers can act on.

• Influence cross-functional stakeholders - engineering, architecture, data science, governance, UX, and senior business leaders.
• Mentor and develop junior product managers.

• 8+ years in technical product management delivering catalog, marketplace, or discovery platforms from ideation to production at scale.
• Deep UX & service design sensibility - passion to build clear, intuitive and scalable UI experiences.
• Multi-channel product delivery - shipped across web UI, API, and/or conversational/agent-based interfaces.
• Technical depth in data infrastructure - data catalogs, metadata management, governance frameworks, data quality tooling.
• Strong communication - translate technical complexity into clear narratives for engineers, designers, and executives.
• Prioritisation at scale - balance competing demands across a large stakeholder base by weighing business impact, user value, and technical feasibility.

• Experience in financial services or highly regulated industries.
• Built or scaled a data catalog, data marketplace, feature store, or developer portals (e.g., Kaggle Datasets, Unity Catalog, Collibra, Alation, Atlan).
• Understanding of agentic AI patterns - tool-use, RAG, function calling - and how marketplace APIs can be exposed to LLM-based agents.
• Experience with search relevance & recommendation systems - ranking algorithms, semantic search, personalisation.
• Hands-on with Snowflake, Databricks, Airflow, Kafka.

• Work on firm-wide platforms used by thousands of data scientists, ML engineers, and analysts across JPMC
• Shape the future of AI/ML and data infrastructure at one of the world's largest financial institutions